edu.illinois.cs.cogcomp.lbjava.nlp.Word.<init>()方法的使用及代码示例
本文整理了Java中edu.illinois.cs.cogcomp.lbjava.nlp.Word.<init>()方法的一些代码示例，展示了Word.<init>()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Word.<init>()方法的具体详情如下：
包路径：edu.illinois.cs.cogcomp.lbjava.nlp.Word
类名称：Word
方法名：<init>
Word.<init>介绍
[英]When all that is known is the spelling of the word.
[中]当我们只知道单词的拼写时。
代码示例
代码示例来源：origin: CogComp/cogcomp-nlp
/**
* Add the provided token to the sentence, for also do any additional word spliting.
*
* @param sentence the sentence to add the word to.
* @param token the individual token.
* @param tag the tag to annotate the word with.
*/
public static void addTokenToSentence(LinkedVector sentence, String token, String tag, ParametersForLbjCode prs) {
NEWord word = new NEWord(new Word(token), null, tag);
word.params = prs;
addTokenToSentence(sentence, word);
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-ner
/**
* Add the provided token to the sentence, for also do any additional word spliting.
*
* @param sentence the sentence to add the word to.
* @param token the individual token.
* @param tag the tag to annotate the word with.
*/
public static void addTokenToSentence(LinkedVector sentence, String token, String tag, ParametersForLbjCode prs) {
NEWord word = new NEWord(new Word(token), null, tag);
word.params = prs;
addTokenToSentence(sentence, word);
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-mlner
/**
* Add the provided token to the sentence, for also do any additional word spliting.
*
* @param sentence the sentence to add the word to.
* @param token the individual token.
* @param tag the tag to annotate the word with.
*/
public static void addTokenToSentence(LinkedVector sentence, String token, String tag) {
NEWord word = new NEWord(new Word(token), null, tag);
addTokenToSentence(sentence, word);
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-standalone-nlp-pipeline
public IllinoisPOSHandler()
{
super("Illinois Part-Of-Speech Tagger", "0.2", "illinoispos");
logger.info("Loading POS model..");
tagger.discreteValue(new Token(new Word("The"), null, ""));
logger.info("POS Tagger ready");
tokensfield = CuratorViewNames.tokens;
sentencesfield = CuratorViewNames.sentences;
}代码示例来源：origin: CogComp/cogcomp-nlp
/**
* Given textual input in the format shown below, this method parses and
* returns the <code>Word</code> that the text represents. Expected
* format: <br><br>
* <p/>
* <code>(pos spelling)</code>
*
* @param text Text representing a word in POS bracket form.
* @param previous The word that came before this word in the sentence.
* @return A <code>Word</code> represented by the input text or
* <code>null</code> if the input does not represent a
* <code>Word</code>.
**/
public static Word parsePOSBracketForm(String text, Word previous) {
if (text.charAt(0) != '(' || text.charAt(text.length() - 1) != ')')
return null;
String[] tokens = text.split(" ");
if (tokens.length != 2) return null;
return new Word(tokens[1].substring(0, tokens[1].length() - 1),
tokens[0].substring(1),
previous);
}
}代码示例来源：origin: CogComp/cogcomp-nlp
/**
* Given an array of <code>String</code>s, this method creates a new
* {@link LinkedVector} containing {@link Word}s.
*
* @param a An array of <code>String</code>s.
* @return A {@link LinkedVector} of {@link Word}s corresponding to the
* input <code>String</code>s.
**/
public static LinkedVector convert(String[] a) {
if (a == null) return null;
if (a.length == 0) return new LinkedVector();
Word w = new Word(a[0]);
for (int i = 1; i < a.length; ++i) {
w.next = new Word(a[i], null, w);
w = (Word) w.next;
}
return new LinkedVector(w);
}代码示例来源：origin: edu.illinois.cs.cogcomp/LBJava-NLP-tools
/**
* Given an array of <code>String</code>s, this method creates a new
* {@link LinkedVector} containing {@link Word}s.
*
* @param a An array of <code>String</code>s.
* @return A {@link LinkedVector} of {@link Word}s corresponding to the
* input <code>String</code>s.
**/
public static LinkedVector convert(String[] a) {
if (a == null) return null;
if (a.length == 0) return new LinkedVector();
Word w = new Word(a[0]);
for (int i = 1; i < a.length; ++i) {
w.next = new Word(a[i], null, w);
w = (Word) w.next;
}
return new LinkedVector(w);
}代码示例来源：origin: edu.illinois.cs.cogcomp/LBJava-NLP-tools
/**
* Given textual input in the format shown below, this method parses and
* returns the <code>Word</code> that the text represents. Expected
* format: <br><br>
* <p/>
* <code>(pos spelling)</code>
*
* @param text Text representing a word in POS bracket form.
* @param previous The word that came before this word in the sentence.
* @return A <code>Word</code> represented by the input text or
* <code>null</code> if the input does not represent a
* <code>Word</code>.
**/
public static Word parsePOSBracketForm(String text, Word previous) {
if (text.charAt(0) != '(' || text.charAt(text.length() - 1) != ')')
return null;
String[] tokens = text.split(" ");
if (tokens.length != 2) return null;
return new Word(tokens[1].substring(0, tokens[1].length() - 1),
tokens[0].substring(1),
previous);
}
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-standalone-nlp-pipeline
public IllinoisChunkerHandler(String configFilename) {
super("Illinois Chunker", "0.3", "illinoischunker");
logger.info("Loading Chunker model..");
tagger.discreteValue(new Token(new Word("The"), null, ""));
logger.info("Chunker ready");
// XXX If no configuration file is give use the default values from CuratorViewNames
if (configFilename.trim().equals("")) {
tokensfield = CuratorViewNames.tokens;
sentencesfield = CuratorViewNames.sentences;
posfield = CuratorViewNames.pos;
}
else {
Properties config = new Properties();
try {
FileInputStream in = new FileInputStream(configFilename);
config.load(new BufferedInputStream(in));
in.close();
} catch (IOException e) {
logger.warn("Error reading configuration file. {}", configFilename);
}
tokensfield = config.getProperty("tokens.field", CuratorViewNames.tokens );
sentencesfield = config.getProperty("sentences.field", CuratorViewNames.sentences );
posfield = config.getProperty("pos.field", CuratorViewNames.pos );
}
}代码示例来源：origin: edu.illinois.cs.cogcomp/LBJava-NLP-tools
Word w = new Word(tokens[1].substring(0, tokens[1].length() - 1),
tokens[0].substring(1),
0,
new Word(tokens[i + 1].substring(0, tokens[i + 1].length() - 1),
tokens[i].substring(1),
w,代码示例来源：origin: CogComp/cogcomp-nlp
/**
* Produces the next object parsed from the input file; in this case, that object is guaranteed
* to be a <code>LinkedVector</code> populated by <code>Token</code>s representing a sentence.
**/
public Object next() {
String[] line = (String[]) super.next();
while (line != null && (line.length < 2 || line[4].equals("-X-")))
line = (String[]) super.next();
if (line == null)
return null;
if (line[3].charAt(0) == 'I')
line[3] = "B" + line[3].substring(1);
Token t = new Token(new Word(line[5], line[4]), null, line[3]);
String previous = line[3];
for (line = (String[]) super.next(); line != null && line.length > 0; line =
(String[]) super.next()) {
if (line[3].charAt(0) == 'I' && !previous.endsWith(line[3].substring(2)))
line[3] = "B" + line[3].substring(1);
t.next = new Token(new Word(line[5], line[4]), t, line[3]);
t = (Token) t.next;
previous = line[3];
}
return new LinkedVector(t);
}
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-chunker
/**
* Produces the next object parsed from the input file; in this case, that object is guaranteed
* to be a <code>LinkedVector</code> populated by <code>Token</code>s representing a sentence.
**/
public Object next() {
String[] line = (String[]) super.next();
while (line != null && (line.length < 2 || line[4].equals("-X-")))
line = (String[]) super.next();
if (line == null)
return null;
if (line[3].charAt(0) == 'I')
line[3] = "B" + line[3].substring(1);
Token t = new Token(new Word(line[5], line[4]), null, line[3]);
String previous = line[3];
for (line = (String[]) super.next(); line != null && line.length > 0; line =
(String[]) super.next()) {
if (line[3].charAt(0) == 'I' && !previous.endsWith(line[3].substring(2)))
line[3] = "B" + line[3].substring(1);
t.next = new Token(new Word(line[5], line[4]), t, line[3]);
t = (Token) t.next;
previous = line[3];
}
return new LinkedVector(t);
}
}代码示例来源：origin: CogComp/cogcomp-nlp
/**
* Produces the next object parsed from the input file; in this case, that object is guaranteed
* to be a <code>LinkedVector</code> populated by <code>Token</code>s representing a sentence.
**/
public Object next() {
String[] line = (String[]) super.next();
while (line != null && line.length == 0)
line = (String[]) super.next();
if (line == null)
return null;
String pos = line[1];
if (pos.equals("-"))
pos = null;
Token t = new Token(new Word(line[0], pos), null, line[2]);
for (line = (String[]) super.next(); line != null && line.length > 0; line =
(String[]) super.next()) {
pos = line[1];
if (pos.equals("-"))
pos = null;
t.next = new Token(new Word(line[0], pos), t, line[2]);
t = (Token) t.next;
}
return new LinkedVector(t);
}
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-chunker
/**
* Produces the next object parsed from the input file; in this case, that object is guaranteed
* to be a <code>LinkedVector</code> populated by <code>Token</code>s representing a sentence.
**/
public Object next() {
String[] line = (String[]) super.next();
while (line != null && line.length == 0)
line = (String[]) super.next();
if (line == null)
return null;
String pos = line[1];
if (pos.equals("-"))
pos = null;
Token t = new Token(new Word(line[0], pos), null, line[2]);
for (line = (String[]) super.next(); line != null && line.length > 0; line =
(String[]) super.next()) {
pos = line[1];
if (pos.equals("-"))
pos = null;
t.next = new Token(new Word(line[0], pos), t, line[2]);
t = (Token) t.next;
}
return new LinkedVector(t);
}
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-mlner
private static Vector<NEWord> splitWord(NEWord word) {
String[] sentence = {word.form + " "};
Parser parser = new WordSplitter(new SentenceSplitter(sentence));
LinkedVector words = (LinkedVector) parser.next();
Vector<NEWord> res = new Vector<>();
if (words == null) {
res.add(word);
return res;
}
String label = word.neLabel;
for (int i = 0; i < words.size(); i++) {
if (label.contains("B-") && i > 0)
label = "I-" + label.substring(2);
NEWord w = new NEWord(new Word(((Word) words.get(i)).form), null, label);
res.addElement(w);
}
return res;
}代码示例来源：origin: CogComp/cogcomp-nlp
private static Vector<NEWord> splitWord(NEWord word) {
String[] sentence = {word.form + " "};
Parser parser = new WordSplitter(new SentenceSplitter(sentence));
LinkedVector words = (LinkedVector) parser.next();
Vector<NEWord> res = new Vector<>();
if (words == null) {
res.add(word);
return res;
}
String label = word.neLabel;
for (int i = 0; i < words.size(); i++) {
if (label.contains("B-") && i > 0)
label = "I-" + label.substring(2);
NEWord w = new NEWord(new Word(((Word) words.get(i)).form), null, label);
res.addElement(w);
}
return res;
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-ner
private static Vector<NEWord> splitWord(NEWord word) {
String[] sentence = {word.form + " "};
Parser parser = new WordSplitter(new SentenceSplitter(sentence));
LinkedVector words = (LinkedVector) parser.next();
Vector<NEWord> res = new Vector<>();
if (words == null) {
res.add(word);
return res;
}
String label = word.neLabel;
for (int i = 0; i < words.size(); i++) {
if (label.contains("B-") && i > 0)
label = "I-" + label.substring(2);
NEWord w = new NEWord(new Word(((Word) words.get(i)).form), null, label);
res.addElement(w);
}
return res;
}代码示例来源：origin: CogComp/cogcomp-nlp
public static void nullifyTaggerCachedFields(SparseNetworkLearner tagger) {
NEWord w = new NEWord(new Word("lala1"), null, "O");
w.parts = new String[0];
NEWord[] words =
{new NEWord(w, null, "O"), new NEWord(w, null, "O"), new NEWord(w, null, "O"),
new NEWord(w, null, "O"), new NEWord(w, null, "O"),
new NEWord(w, null, "O"), new NEWord(w, null, "O")};
for (int i = 1; i < words.length; i++) {
words[i].parts = new String[0];
words[i].previous = words[i - 1];
words[i].previousIgnoreSentenceBoundary = words[i - 1];
words[i - 1].next = words[i];
words[i - 1].nextIgnoreSentenceBoundary = words[i];
}
for (NEWord word : words)
word.neTypeLevel1 = word.neTypeLevel2 = "O";
tagger.classify(words[3]);
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-mlner
public static void nullifyTaggerCachedFields(SparseNetworkLearner tagger) {
NEWord w = new NEWord(new Word("lala1"), null, "O");
w.parts = new String[0];
NEWord[] words =
{new NEWord(w, null, "O"), new NEWord(w, null, "O"), new NEWord(w, null, "O"),
new NEWord(w, null, "O"), new NEWord(w, null, "O"),
new NEWord(w, null, "O"), new NEWord(w, null, "O")};
for (int i = 1; i < words.length; i++) {
words[i].parts = new String[0];
words[i].previous = words[i - 1];
words[i].previousIgnoreSentenceBoundary = words[i - 1];
words[i - 1].next = words[i];
words[i - 1].nextIgnoreSentenceBoundary = words[i];
}
for (NEWord word : words)
word.neTypeLevel1 = word.neTypeLevel2 = "O";
tagger.classify(words[3]);
}代码示例来源：origin: edu.illinois.cs.cogcomp/illinois-ner
public static void nullifyTaggerCachedFields(SparseNetworkLearner tagger) {
NEWord w = new NEWord(new Word("lala1"), null, "O");
w.parts = new String[0];
NEWord[] words =
{new NEWord(w, null, "O"), new NEWord(w, null, "O"), new NEWord(w, null, "O"),
new NEWord(w, null, "O"), new NEWord(w, null, "O"),
new NEWord(w, null, "O"), new NEWord(w, null, "O")};
for (int i = 1; i < words.length; i++) {
words[i].parts = new String[0];
words[i].previous = words[i - 1];
words[i].previousIgnoreSentenceBoundary = words[i - 1];
words[i - 1].next = words[i];
words[i - 1].nextIgnoreSentenceBoundary = words[i];
}
for (NEWord word : words)
word.neTypeLevel1 = word.neTypeLevel2 = "O";
tagger.classify(words[3]);
}内容来源于网络，如有侵权，请联系作者删除！
